Modeling the Bilingual Lexicon of an Individual Subject

Lexicon is a central component in any language processing system, whether human or artificial. Recent empirical evidence suggests that a multilingual lexicon consists of a single component representing word meanings, and separate component for the symbols in each language. These components can be modeled as self-organizing maps, with associative connections between them implementing comprehension and production. Computational experiments in this paper show that such a model can trained to match the proficiency and age of acquisition of particular bilingual individuals. In the future, it may be possible to use such models to predict the effect of rehabilitation of bilingual aphasia, resulting in more effective treatments.